ai-300 Practice Question 2018
Exam: ai-300
Domain: Monitor and manage ML deployments
Topic: Monitor model performance and data drift
Difficulty: medium
Your organization wants to ensure that the features used in their machine learning models are contributing meaningfully to the predictions. They are particularly interested in understanding how each feature impacts the model's output. Which tool or method would you recommend to achieve this, and what is the key benefit of using this approach?
Answer Options
A
Implement a confusion matrix analysis
B
Use SHAP (SHapley Additive exPlanations) for feature attribution
C
Perform a ROC curve analysis
D
Apply cross-validation techniques
Correct Answer
B: Use SHAP (SHapley Additive exPlanations) for feature attribution
Explanation
The correct answer is to use feature attribution methods such as SHAP (SHapley Additive exPlanations). This method provides insights into how each feature contributes to the model's output, which helps in understanding the model's behavior and ensuring that the features are meaningful. The other options are incorrect because they do not provide the specific method for feature attribution.